IP Library › Granted Patent US 12,725,157
Granted Patent B2
US 12,725,157 · App. 18/972,746 · Granted Sep 1, 2026

Distributed ledger technology utilizing cardless payments

Inventors: Duc M. Trinh (Golden Valley, MN); Nikolai Stroke (Gilbert, AZ); Harmit Singh Dhanoa (Mountain House, CA)
Assignee: Wells Fargo Bank, N.A.
G06Q20/40145G06Q20/3821G06Q20/3829G06F21/32
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Quick Facts
Patent No.
US 12,725,157
App. No.
18/972,746
Granted
Sep 1, 2026
Kind
B2
Abstract

Systems, methods and computer-readable storage media utilized to complete a cardless transaction on a distributed ledger network. One method includes receiving, by a point-of-sale (POS) computing device, a transaction request including a biometric sample from an individual associated with a payment account at a financial institution. The method further includes authenticating, by the POS computing device, the biometric sample by cross-referencing the biometric sample with a biometric dataset stored on the distributed ledger network. The method further includes, in response to authenticating the biometric sample, generating, by the POS computing device, a cryptogram associated with the biometric sample and processing, by the POS computing device, the transaction request utilizing the cryptogram.

Claims (58)

1 . A method, comprising:

receiving, by a point-of-sale (POS) computing device, a sample from an individual using a sensor at the POS computing device, the individual associated with a payment account at a provider institution, wherein the POS computing device is a node of a plurality of nodes on a distributed ledger network, wherein the sensor is at least one of a fingerprint sensor, a facial recognition sensor or camera, an iris sensor, a hand sensor, or a sound sensor;

comparing, by the POS computing device, the sample with a dataset stored on the distributed ledger network;

identifying, by the POS computing device utilizing a first model trained to identify particular samples, the sample is a particular sample;

determining, by the POS computing device utilizing a second model trained to identify particular individuals based on the particular sample identified and outputted by the first model, that the sample matches an enrolled sample of the dataset, wherein each of the first model and second model corresponds to at least one of an artificial intelligence model or a machine-learning model trained to output indicating a match between the sample and the enrolled sample;

in response to determining that the sample matches the enrolled sample, generating, by the POS computing device, a cryptogram based on an encryption key and a payment instrument identifier of the payment instrument, wherein the cryptogram is unique to the sample and the cardless transaction request, wherein each cryptogram is associated with at least one sample of a plurality of samples of the dataset, wherein the cryptogram is a new cryptogram unique to the cardless transaction request based on the cardless transaction request and the sample; and

executing, by the POS computing device, a transaction processing application to process a cardless transaction request utilizing the cryptogram, wherein processing comprises transmitting the cardless transaction request comprising the cryptogram to a computing device associated with the provider institution.

2 . The method of claim 1 , further comprising:

receiving, by the POS computing device, an enrollment request comprising payment account information of the individual; and

sending, by the POS computing device to the distributed ledger network, the payment account information and the sample.

3 . The method of claim 2 , wherein the payment account information comprises information corresponding to a payment card associated with the individual.

4 . The method of claim 1 , wherein the dataset comprises a plurality of reference data identifying a plurality of individuals, and each reference data is associated with a unique encryption key and a particular individual of the plurality of individuals.

5 . The method of claim 1 , wherein comparing the sample with the dataset stored on the distributed ledger network comprises matching the sample with reference data of the plurality of reference data uniquely identifying the individual.

6 . The method of claim 1 , further comprising:

receiving, by the POS computing device, a second cardless transaction request comprising a second sample from the individual;

authenticating, by the POS computing device, the second sample by comparing the second sample with the dataset;

in response to authenticating the second sample, generating, by the POS computing device, a second cryptogram associated with the second sample; and

executing, by the POS computing device, the transaction processing application to process the second cardless transaction request utilizing the second cryptogram.

7 . The method of claim 1 , wherein the cardless transaction request is associated with at least one of a purchase of a good, or a purchase of a service.

8 . A computing system comprising:

at least one processor; and

at least one memory storing instructions, when executed by the at least one processor, causes the at least one processor to:

receive, a sample from an individual using a sensor, the individual associated with a payment account at a provider institution, wherein the sensor is at least one of a fingerprint sensor, a facial recognition sensor or camera, an iris sensor, a hand sensor, or a sound sensor;

compare the sample with a dataset stored on a distributed ledger network;

identify, utilizing a first model trained to identify particular samples, the sample is a particular sample;

determine, utilizing a second model trained to identify particular individuals based on the particular sample identified and outputted by the first model, that the sample matches an enrolled sample of the dataset, wherein each of the first model and second model corresponds to at least one of an artificial intelligence model or a machine-learning model trained to output indicating a match between the sample and the enrolled sample;

in response to determining that the sample matches the enrolled sample, generate a cryptogram based on an encryption key and a payment instrument identifier of the payment instrument, wherein the cryptogram is unique to the sample and the cardless transaction request, wherein each cryptogram is associated with at least one sample of a plurality of samples of the dataset, wherein the cryptogram is a new cryptogram unique to the cardless transaction request based on the cardless transaction request and the sample; and

execute a transaction processing application to process a cardless transaction request utilizing the cryptogram, wherein processing comprises transmitting the cardless transaction request comprising the cryptogram to a computing device associated with the provider institution.

9 . The system of claim 8 , wherein the at least one processor configured to:

receive an enrollment request comprising payment account information of the individual; and

send, to the distributed ledger network, the payment account information and the sample.

10 . The system of claim 9 , wherein the payment account information comprises information corresponding to a payment card associated with the individual.

11 . The system of claim 8 , wherein the dataset comprises a plurality of reference data identifying a plurality of individuals, and each reference data is associated with a unique encryption key and a particular individual of the plurality of individuals.

12 . The system of claim 8 , wherein comparing the sample with the dataset stored on the distributed ledger network comprises matching the sample with reference data of the plurality of reference data uniquely identifying the individual.

13 . The system of claim 8 , wherein the at least one processor configured to:

receive a second cardless transaction request comprising a second sample from the individual;

authenticate the second sample by comparing the second sample with the dataset;

in response to authenticating the second sample, generate a second cryptogram associated with the second sample; and

execute the transaction processing application to process the second cardless transaction request utilizing the second cryptogram.

14 . The system of claim 8 , wherein the cardless transaction request is associated with at least one of a purchase of a good, or a purchase of a service.

15 . One or more non-transitory computer-readable storage media having instructions stored thereon that, when executed by at least one processor, cause the at least one processor to:

receive, a sample from an individual using a sensor, the individual associated with a payment account at a provider institution, wherein the sensor is at least one of a fingerprint sensor, a facial recognition sensor or camera, an iris sensor, a hand sensor, or a sound sensor;

compare the sample with a dataset stored on a distributed ledger network;

identify, utilizing a first model trained to identify particular samples, the sample is a particular sample;

determine, utilizing a second model trained to identify particular individuals based on the particular sample identified and outputted by the first model, that the sample matches an enrolled sample of the dataset, wherein each of the first model and second model corresponds to at least one of an artificial intelligence model or a machine-learning model trained to output indicating a match between the sample and the enrolled sample;

in response to determining that the sample matches the enrolled sample, generate a cryptogram based on an encryption key and a payment instrument identifier of the payment instrument, wherein the cryptogram is unique to the sample and the cardless transaction request, wherein each cryptogram is associated with at least one sample of a plurality of samples of the dataset, wherein the cryptogram is a new cryptogram unique to the cardless transaction request based on the cardless transaction request and the sample; and

execute a transaction processing application to process a cardless transaction request utilizing the cryptogram, wherein processing comprises transmitting the cardless transaction request comprising the cryptogram to a computing device associated with the provider institution.

16 . The non-transitory computer-readable storage media of claim 15 , wherein the at least one processor caused to:

receive an enrollment request comprising payment account information of the individual; and

send, to the distributed ledger network, the payment account information and the sample.

17 . The non-transitory computer-readable storage media of claim 16 , wherein the payment account information comprises information corresponding to a payment card associated with the individual.

18 . The non-transitory computer-readable storage media of claim 15 , wherein the dataset comprises a plurality of reference data identifying a plurality of individuals, and each reference data is associated with a unique encryption key and a particular individual of the plurality of individuals.

19 . The non-transitory computer-readable storage media of claim 15 , wherein comparing the sample with the dataset stored on the distributed ledger network comprises matching the sample with reference data of the plurality of reference data uniquely identifying the individual.

20 . The non-transitory computer-readable storage media of claim 15 , wherein the at least one processor caused to:

receive a second cardless transaction request comprising a second sample from the individual;

authenticate the second sample by comparing the second sample with the dataset;

in response to authenticating the second sample, generate a second cryptogram associated with the second sample; and

execute the transaction processing application to process the second cardless transaction request utilizing the second cryptogram.

Continuity (2)
Continuation 16880257 · May 21, 2020
Related Publication 20250094988A1 · Mar 20, 2025
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